install Compile Taskflow with CUDA Benchmark Taskflow Supported Compilers install_1BAISupportedCompilers Integrate Taskflow to Your Project install_1BAIIntegrateTaskflowToYourProject Build Examples and Unit Tests install_1BAIBuildExamplesAndUnitTests Build CUDA Examples and Unit Tests install_1BAIBuildCUDACode Build Sanitizers install_1BAIBuildSanitizers Build Benchmarks install_1BAIBuildBenchmarks Build Documentation install_1BAIBuildDocumentation This page describes how to set up Taskflow in your project. We will also go through the building process of unit tests and examples. To use Taskflow, you only need a compiler that supports C++17: GNU C++ Compiler at least v8.4 with -std=c++17 Clang C++ Compiler at least v6.0 with -std=c++17 Microsoft Visual Studio at least v15.7 (MSVC++ 19.14) AppleClang Xcode Version at least v12.0 with -std=c++17 Nvidia CUDA Toolkit and Compiler (nvcc) at least v11.1 with -std=c++17 Intel C++ Compiler (nvcc) at least v19.0.1 with -std=c++17 Intel DPC++ Clang Compiler at least v13.0.0 with -std=c++17 and SYCL20 Taskflow works on Linux, Windows, and Mac OS X. Taskflow is header-only and there is no need for installation. Simply download the source and copy the headers under the directory taskflow/ to your project. ~$gitclonehttps://github.com/taskflow/taskflow.git ~$cdtaskflow/ ~$cp-rtaskflowmyproject/include/ Taskflow is written in C++17 and is built on top of C++ standardized threading libraries to improve portability. To compile a Taskflow program, say simple.cpp, you need to tell the compiler where to find the Taskflow header files and link it through the system thread library (usually POSIX threads in Linux-like systems). Take gcc for an example: ~$g++simple.cpp-std=c++17-Imyproject/include/-O2-pthread-osimple Taskflow uses CMake to build examples and unit tests. We recommend using out-of-source build. ~$cdpath/to/taskflow ~$mkdirbuild ~$cdbuild ~$cmake../ ~$make#compileallexamplesandunittests ~$maketest Runningtests... /usr/bin/ctest--force-new-ctest-process Testproject/home/tsung-wei/Code/taskflow/build Start1:passive_vector 1/254Test#1:passive_vector...................Passed0.04sec Start2:function_traits 2/254Test#2:function_traits..................Passed0.00sec Start3:object_pool.sequential 3/254Test#3:object_pool.sequential...........Passed0.10sec ... 100%testspassed,0testsfailedoutof254 TotalTesttime(real)=29.67sec When the building completes, you can find the executables for examples and tests under the two folders, examples/ and unittests/. You can list a set of available options in the cmake. ~$cmake-LA ... TF_BUILD_EXAMPLES:BOOL=ON#bydefault,wecompileexamples TF_BUILD_TESTS:BOOL=ON#bydefault,wecompiletests TF_BUILD_BENCHMARKS:BOOL=OFF#bydefault,wedon'tcompilebenchmarks TF_BUILD_CUDA:BOOL=OFF#bydefault,wedon'tcompileCUDAcode ... ...moreoptions Currently, our CMake script supports the following options: CMake Option Default Usage TF_BUILD_EXAMPLES ON enable/disable building examples TF_BUILD_TESTS ON enable/disable building unit tests TF_BUILD_BENCHMARKS OFF enable/disable building benchmarks TF_BUILD_CUDA OFF enable/disable building CUDA code To enable or disable a specific option, use -D in the CMake build. For example: ~$cmake../-DTF_BUILD_EXAMPLES=OFF The above command turns off building Taskflow examples. To build CUDA code, including unit tests and examples, enable the CMake option TF_BUILD_CUDA to ON. Cmake will automatically detect the existence of nvcc and use it to compile and link .cu code. ~$cmake../-DTF_BUILD_CUDA=ON ~$make Please visit the page Compile Taskflow with CUDA for details. You can build Taskflow with sanitizers to detect a variety of errors, such as data race, memory leak, undefined behavior, and others. To enable a sanitizer, add the sanitizer flag to the CMake variable CMAKE_CXX_FLAGS. The following example enables thread sanitizer in building Taskflow code to detect data race: #buildTaskflowcodewiththreadsanitizertodetectdatarace ~$cmake../-DCMAKE_CXX_FLAGS="-fsanitize=thread-g" #buildTaskflowcodewithaddresssanitizertodetectillegalmemoryaccess ~$cmake../-DCMAKE_CXX_FLAGS="-fsanitize=address-g" #buildTaskflowcodewithubsanitizertodetectundefinedbehavior ~$cmake../-DCMAKE_CXX_FLAGS="-fsanitize=undefined-g" Our continuous integration workflows incorporates thread sanitizer (-fsanitize=thread), address sanitizer (-fsanitize=address), and leak sanitizer (-fsanitize=leak) to detect data race, illegal memory address, and memory leak. To our best knowledge, Taskflow is one of the very few parallel programming libraries that are free from data race. Some sanitizers are supported by certain computing architectures. You can find the information about architecture support of each sanitizer at Clang Documentation and GCC Instrumentation Options. The Taskflow project contains a set of benchmarks to evaluate and compare the performance of Taskflow with existing parallel programming libraries. To build the benchmark code, enable the CMake option TF_BUILD_BENCHMARKS to ON as follows: ~$cmake../-DTF_BUILD_BENCHMARKS=ON ~$make Please visit the page Benchmark Taskflow for details. Taskflow uses Doxygen and m.css to generate this documentation. The source of documentation is located in the folder taskflow/doxygen and the generated html is output to the folder taskflow/docs. To generate the documentation, you need to first install doxygen: #ubuntuasanexample ~$sudoapt-getinstalldoxygengraphviz Once you have doxygen and dot graph generator installed, clone the m.css project and enter the m.css/documentation directory: ~$gitclonehttps://github.com/mosra/m.css.git ~$cdm.css/documentation The script doxygen.py requires Python 3.6, depends on Jinja2 for templating and Pygments for code block highlighting. You can install the dependencies via pip or your distribution package manager: #Youmayneedsudohere #Moredetailsareavailableathttps://mcss.mosra.cz/documentation/doxygen/ ~$pip3installjinja2Pygments Next, invoke doxygen.py and point it to the taskflow/doxygen/conf.py: ~$./doxygen.pypath/to/taskflow/doxygen/conf.py You can find the documentation output in taskflow/docs.